Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Monte Carlo

FEBRUARY 9, 2023

Over the past several years, data warehouses have evolved dramatically, but that doesn’t mean the fundamentals underpinning sound data architecture needs to be thrown out the window. While data vault has many benefits, it is a sophisticated and complex methodology that can present challenges to data quality.

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Data Engineering Podcast

JUNE 17, 2023

Summary Architectural decisions are all based on certain constraints and a desire to optimize for different outcomes. In data systems one of the core architectural exercises is data modeling, which can have significant impacts on what is and is not possible for downstream use cases. ML, reverse ETL, etc.)

Data Lake 130

Data Lake Metadata Data Architecture Machine Learning 130

AltexSoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Data warehouse vs. data lake in a nutshell.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Rockset

APRIL 26, 2023

We’ve noticed many common patterns across streaming data architectures and we’ll be sharing a blueprint for three of the most popular: anomaly detection, IoT, and recommendations. The majority of anomaly detectors require streaming data, real-time data and historical data in order to generate inferences.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

JANUARY 31, 2022

This blog walks you through what does Snowflake do , the various features it offers, the Snowflake architecture, and so much more. Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse? Its analytical skills enable companies to gain significant insights from their data and make better decisions.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. Each of these architectures has its own unique strengths and tradeoffs.

Data Lake 89

Data Lake Data Warehouse Cloud Unstructured Data 89

Rockset

JULY 21, 2020

Metadata services used for service discovery are close to the bottom of that stack and they need to provide 1 or 2 orders of magnitude higher reliability than any service built on top of that. In your application stack, assume for every level you have in your stack, you will lose one 9 in your application’s reliability.

Data Architecture 40

Data Architecture Architecture Building Programming Language 40

Netflix Tech

NOVEMBER 14, 2023

Psyberg automates our data loads, making it suitable for various data processing needs, including intraday pipeline use cases. It leverages Iceberg metadata to facilitate processing incremental and batch-based data pipelines. Psyberg: The Game Changer! This is mainly used to identify new changes since the last update.

Data Engineering 105

Data Engineering Data Engineer Engineering Metadata 105

AltexSoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

JUNE 7, 2022

In our very own Enterprise Data Maturity research surveying over 3,000 IT and senior business leaders, we found that 40% of organizations are currently running hybrid but mostly on-premises, and 36% of respondents expect to shift to hybrid multi-cloud in the next 18 months. Where data flows, ideas follow.

IT 108

IT Unstructured Data Data Architecture Government 108

Monte Carlo

APRIL 16, 2022

The challenge with passive ETL or transformations in the warehouse The modern data warehouse architecture creates problems across many layers. There are several problems with an architecture and process that heavily relies on transforming data once it has entered the data warehouse.

Data Warehouse 52

Data Warehouse Architecture Data Government 52

Data Engineering Weekly

DECEMBER 10, 2023

[link] Thoughtworks: Anonymesh - Data sharing meets privacy and security During my stay in India, I had multiple conversations with fintech data practitioners in India, and many pointed out the challenges with data sharing while preserving privacy & security. Stores metadata to utilize later.

Data Engineering 76

Data Engineering Data Engineer Engineering Metadata 76

Snowflake

DECEMBER 12, 2023

To give customers flexibility for how they fit Snowflake into their data architecture, Iceberg Tables can be configured to use either Snowflake or an external service such as AWS Glue as the table’s catalog to track metadata, with an easy, one-line SQL command to convert the table’s catalog to Snowflake in a metadata-only operation.

Metadata 89

Metadata Python AWS Government 89

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Scala 98

Data Engineering Podcast

SEPTEMBER 23, 2018

Can you walk through the stages of an ideal lifecycle for data within the context of an organizations uses for it? What are some of the common mistakes that are made when designing a data architecture and how do they lead to failure?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Towards Data Science

OCTOBER 25, 2023

Not too long ago, almost all data architectures and data team structures followed a centralized approach. As a data or analytics engineer, you knew where to find all the transformation logic and models because they were all in the same codebase. Your organization may be undergoing the decentralization of data.

Data Pipeline 82

Data Pipeline SQL Data Architecture Data 82

Monte Carlo

FEBRUARY 19, 2024

Entire Slack groups dedicated to decentralized architecture. Now, let me just say on the front end, the data mesh is not an Avatar 2 situation. (14 The data mesh is a thoughtful decentralized approach that facilitates the creation of domain-driven, self-service data products. How do we get the data we need faster?

Architecture 59

Architecture Government Data Data Architecture 59

Monte Carlo

MARCH 13, 2024

When to implement data governance Data governance is now considered a must-have for most organizations because it helps improve compliance with GDPR and other measures, safeguard proprietary data against bad actors, support a distributed data architecture, and maintain data quality.

Data Governance 52

Data Governance Government Metadata Data 52

Databand.ai

JULY 19, 2023

This capability is useful for businesses, as it provides a clear and comprehensive view of their data’s history and transformations. Data lineage tools are not a new concept. In this article: Why Are Data Lineage Tools Important? It provides context for data, making it easier to understand and manage.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Snowflake

JANUARY 22, 2024

In 2020, Fidelity kicked off its digital transformation and established an Enterprise Data Lake (EDL) along with Data Labs. All of Fidelity’s storage abides by its data security framework and data governance policies, and provides a holistic approach to metadata management.

Engineering 62

Engineering Data Lake Unstructured Data Metadata 62

Data Engineering Weekly

DECEMBER 29, 2022

Data Catalog as a passive web portal to display metadata requires significant rethinking to adopt modern data workflow, not just adding “modern” in its prefix. I know that is an expensive statement to make😊 To be fair, I’m a big fan of data catalogs, or metadata management , to be precise.

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Cloudera

SEPTEMBER 15, 2022

Modern data platforms deliver an elastic, flexible, and cost-effective environment for analytic applications by leveraging a hybrid, multi-cloud architecture to support data fabric, data mesh, data lakehouse and, most recently, data observability. Luke: What is a modern data platform?

Data Lake 79

Data Lake Analytics Application Cloud Storage Architecture 79

Ascend.io

FEBRUARY 28, 2024

Metadata Management for Enhanced Machine Interpretation Data engineering extends its importance to the realm of metadata management, providing AI models with essential context about data definitions, classifications, and governance policies.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Ascend.io

APRIL 19, 2023

By adopting a post-modern data stack, engineering leaders can reduce their reliance on a multitude of vendors (and the exorbitant costs that accompany them) and open-source tools, minimize time-consuming integration work, and accelerate their overall data architecture.

Metadata 52

Metadata Business Analyst Hadoop Software Engineer 52

Monte Carlo

JANUARY 23, 2023

But while most every company would consider themselves a “data-first” organization, not every data architecture is treated to the same level of democratization and scalability. In this post we’ll look at the dizzyingly buzzy data mesh and how it stacks up to the more traditional aggregated architectural approach of a data lake.

Data Lake 52

Data Lake Unstructured Data Business Intelligence Architecture 52

Data Engineering Podcast

JULY 28, 2019

In this episode Tim Ward, CEO of CluedIn, explains the idea of eventual connectivity as a new paradigm for data integration. Rather than manually defining all of the mappings ahead of time, we can rely on the power of graph databases and some strategic metadata to allow connections to occur as the data becomes available.

Data Integration 100

Data Integration Metadata Media Architecture 100

Towards Data Science

FEBRUARY 15, 2023

In this context, data management in an organization is a key point for the success of its projects involving data. One of the main aspects of correct data management is the definition of a data architecture. The Lakehouse architecture was one of them. show() The history object is a Spark Data Frame.

Data Lake 80

Data Lake Data Warehouse Hadoop Data Architecture 80

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Education 61

Education Unstructured Data Data Lake Data Warehouse 61

Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs.

Data Architecture 82

Data Architecture Architecture Management Banking 82

Data Engineering Weekly

JANUARY 15, 2023

SiliconANGLE theCUBE: Analyst Predictions 2023 - The Future of Data Management By far one of the best analyses of trends in Data Management. 2023 predictions from the panel are; Unified metadata becomes kingmaker. The author writes a few best practices for managing medallion-style architecture.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 90

Data Lake Data Warehouse BI SQL 90

Monte Carlo

MAY 25, 2023

That’s why we’re excited to announce that uniting diverse data team personas to collectively ensure data quality just got easier, thanks to a new integration between Monte Carlo’s data observability platform and Atlan’s active metadata platform.

Metadata 52

Metadata Data Governance Government Business Intelligence 52

Data Engineering Podcast

SEPTEMBER 1, 2021

That leaves DataOps reactive to data quality issues and can make your consumers lose confidence in your data. By connecting to your pipeline orchestrator like Apache Airflow and centralizing your end-to-end metadata, Databand.ai lets you identify data quality issues and their root causes from a single dashboard.

Data Lake 100

Data Lake Cloud AWS SQL 100

Cloudera

JANUARY 5, 2023

This is where leveraging modern data architectures like data lakehouse, data fabric, and data mesh is essential to driving business efficiencies across diverse operations. These features provide businesses with a common metadata, security, and governance model across all their data.

Banking 52

Banking Machine Learning Insurance Data Architecture 52

ProjectPro

NOVEMBER 7, 2016

Understanding the Hadoop architecture now gets easier! This blog will give you an indepth insight into the architecture of hadoop and its major components- HDFS, YARN, and MapReduce. We will also look at how each component in the Hadoop ecosystem plays a significant role in making Hadoop efficient for big data processing.

Hadoop 40

Hadoop Architecture IT Big Data 40